Comparison of Machine Learning Models for Prediction of Initial Intravenous Immunoglobulin Resistance in Children With Kawasaki Disease

We constructed an optimal machine learning (ML) method for predicting intravenous immunoglobulin (IVIG) resistance in children with Kawasaki disease (KD) using commonly available clinical and laboratory variables. We retrospectively collected 98 clinical records of hospitalized children with KD (2–1...

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Detalles Bibliográficos
Autores principales: Kuniyoshi, Yasutaka, Tokutake, Haruka, Takahashi, Natsuki, Kamura, Azusa, Yasuda, Sumie, Tashiro, Makoto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Pediatrics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744372/
https://www.ncbi.nlm.nih.gov/pubmed/33344380
http://dx.doi.org/10.3389/fped.2020.570834

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744372/
https://www.ncbi.nlm.nih.gov/pubmed/33344380
http://dx.doi.org/10.3389/fped.2020.570834

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